Specialist in Business Analytics
Delivery mode
- Face-to-face and online
Language
- Spanish
Credits
- 20
Places
- 35
Specialist in Business Analytics
CUNEF Universidad’s Business AnalyticsSpecialist programme delves into the data analytics techniques, systems and tools required to develop projects and make business decisions based on large volumes of information, helping our students become Artificial Intelligence Analysts. The aim is to equip participants with the skills and knowledge they need to make sense of corporate and industry data and provide strategic advice.
NTT Data Europe & Latam is CUNEF Universidad’s institutional partner in this programme. Experts from the organisation participate as lecturers, contributing their extensive experience in business analytics projects in all industries. NTT DATA is the 6th largest IT services provider in the world, with 140,000 professionals operating in more than 50 countries. NTT DATA Europe & Latam was born from the alliance between everis and NTT DATA EMEA to bring transformation and innovation to clients in Europe and Latin America.
Curriculum
Using a practical and highly rigorous approach, the programme moves forward progressively, to achieve a paradigm shift from management by instinct to management based on data and their impact on business. The programme is designed to enhance participants’ professional skills and provide them with practical insights regarding:
- The fundamentals of data analytics projects and their impact on business decisions in data-driven project management.
- How to structure corporate information.
- How to extract value from data using R and Python programming.
- How to create business analysis reports with advanced visualisation techniques.
- How to use artificial intelligence (machine learning) in business analytics projects.
The Business Analytics Specialist programme includes the following modules:
| Content | ECTS |
|---|---|
| This module aims to familiarise participants with the principles, practices and approaches that are commonly used for data analysis in the corporate world. They will study the algorithms and statistical models used to analyse and make business decisions in different industries and roles. Once they successfully complete this module, participants will: - Understand the techniques used most frequently in exploratory data analysis models. - Master the concepts required to develop demand forecasting models. - Become familiar with predictive analysis processes for decision making. - Understand the methods used in the creation of data-driven business projects. | 4 |
| Content | ECTS |
|---|---|
| This module enables professionals with all sorts of backgrounds and training to become familiar with relational databases and SQL language. The module aims to ensure that participants: - Master the principles of corporate database design. - Understand the scope and specifications of relational databases, as well as the capacity of SQL language. - Learn how to use relational databases as data repositories, so they can be used as a basis for data analysis in corporate environments from a business expert’s perspective. - Acquire the knowledge, procedures and good practices that will enable them to operate relational databases using SQL language. They will learn to organise the transformation and retrieval of the data so they can be analysed using tools such as R or Python or visualised using tools such as Tableau or Power BI. - Develop the necessary technical skills to integrate and aggregate data and access information on related tables. - Understand the problems that may arise when migrating data from a management system to an analysis system. - Learn to consider different data preparation strategies. | 4 |
| Content | ECTS |
|---|---|
| The purpose of this module is to teach professionals the basic skills required to understand and apply one of the most relevant languages used in business analytics: Python. The specific learning outcomes are: - Understand the use of Python in data projects. - Transition from spreadsheets to a programming language. - Use code to solve specific data tasks. - Propose data structures (importing and exporting datasets). - Master the use of Pandas to transform data. | 5 |
| Content | ECTS |
|---|---|
| Humans are essentially visual by nature, which is why we respond to and process visual data better than any other type of data. The difference between a good report and an excellent one lies in visualisation. During this module, participants work with different visualisation tools, always with the help of expert professionals, to create the most appropriate presentations and reports for each audience. These tools can be used to integrate information from different sources, relate it and automate it according to specific management criteria. Participants will learn to: - Model data in Power BI. - Design effective charts, indicators and dashboards. - Build business intelligence applications. - Create effective business analytics presentations using Power BI. - Incorporate business analytics to big data and the corporate world. | 4 |
| Content | ECTS |
|---|---|
| This module uses a practical approach that enables participants to acquire data analysis skills for business decision making using artificial intelligence systems (machine learning). In a hyperconnected world, it is vital to understand what information is available, learn how to collect the relevant data and know how to extract value from them. Participants become familiar with supervised learning and data classification techniques, as well as statistical concepts and algorithms aimed at identifying behavioural patterns and processes to infer trends and make business predictions. They will: - Become familiar with machine learning techniques applied to business analytics (terminology and main concepts). - Know and understand the requirements for the use of machine learning techniques to create business intelligence projects (pattern recognition, dimensionality reduction, feature selection...). - Know the modelling techniques that are frequently used to manage structured and unstructured data (descriptive analysis, neural networks, deep learning, clustering...). - Learn the techniques used to transform unstructured data (texts, sounds, images...) into data that can be analysed and used in business intelligence projects. | 5 |
A quién está dirigido
El Programa de especialización en Business Analytics está dirigido a profesionales experimentados que deseen especializarse y fortalecer su desarrollo profesional a través de la aplicación práctica de las técnicas de business analytics a la actividad empresarial. Los contenidos del programa y su aplicación son aplicables a multitud de actividades y sectores, entre ellos: servicios bancarios y financieros, consultoría, publicidad, IT y telecomunicaciones, gran consumo, salud, educación… Los participantes en el programa responden, por tanto, a perfiles profesionales diversos, entre ellos:
- Directivos y managers funcionales que buscan mejorar sus competencias en la toma de decisiones de negocios utilizando el poder de los datos.
- Consultores y asesores que desean mejorar sus conocimientos de analítica de negocios.
- Profesionales técnicos que precisan implementar la analítica en su función u organización.
- Responsables técnicos (ventas, marketing, operaciones, logística, RRHH, producción…) que precisan integrar las capacidades de análisis en su desempeño profesional.
El Programa se desarrolla a través de la metodología híbrida
A lo largo de un período lectivo (octubre – febrero) en el que se abordan los contenidos previstos en los diferentes módulos. Todo ello, de acuerdo con una programación en la que abordan los diferentes módulos a través de una metodología híbrida que combina actividades presenciales o live on line con actividades virtuales.
- Actividades presenciales o live online
. Las sesiones síncronas se desarrollan los viernes por la tarde de 16:00h a 21:00h y un sábado al mes de 10:30 a 13:30h. Los participantes asisten presencialmente en el Campus o live online a través de vídeo-colaboración. Estas opciones permiten adaptar la participación con independencia de la ubicación geográfica. Las sesiones quedan grabadas y disponibles a través del Campus virtual de CUNEF Universidad.
- Actividades virtuales
. En cada módulo, los participantes trabajan con los contenidos virtualizados y llevan a cabo diversos proyectos en formato online tutorizados por los profesores responsables del módulo.
- Estudio y trabajo personal con materiales online, lecturas, visionado de vídeos explicativos, casos prácticos, foros de debate y pruebas de auto-test.
- Desarrollo de modelos y trabajo con herramientas técnicas.
- Análisis de casos y situaciones prácticas profesionales.
- Sesiones de debate y trabajo aplicado hands-on con los profesores y expertos colaboradores.
- Capstone Project. Durante el programa los participantes desarrollan un proyecto con enfoque práctico adaptado a sus ámbitos de actividad profesional.
Empleabilidad
Como participante en el Programa de especialización en Business Analytics disfrutarás del alto grado de empleabilidad -96,67%- y de la excelente proyección profesional de los postgraduados de CUNEF Universidad.
Las técnicas de business analytics están experimentando un auge sin precedentes y constituyen una importante palanca de transformación en el mundo de los negocios. La revolución digital está produciendo profundos cambios en los hábitos de consumo y en los modelos de negocios en todo tipo de industrias. Lo anterior, unido a la hiperconectividad y el exponencial aumento de la capacidad computacional de los sistemas, genera tremendas oportunidades laborales.
El Programa de especialización en Business Analytics que aquí te presentamos está destinado a los profesionales que desean obtener valor diferencial de dichas potencialidades en las estrategias y proyectos de negocio de sus compañías y corporaciones.